{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            High   Low  Open  Close      Volume  Adj Close\n",
      "Date                                                      \n",
      "2017-01-03  4.79  4.75  4.76   4.77   7883000.0   4.448430\n",
      "2017-01-04  4.85  4.79  4.80   4.84  10247100.0   4.513710\n",
      "2017-01-05  4.92  4.83  4.85   4.90   9878400.0   4.569665\n",
      "2017-01-06  4.99  4.90  4.93   4.92  18078800.0   4.588317\n",
      "2017-01-09  4.88  4.78  4.86   4.83  14554000.0   4.504384\n",
      "            High   Low  Open  Close      Volume  Adj Close\n",
      "Date                                                      \n",
      "2019-01-03  5.65  5.56  5.64   5.57  17354500.0       5.57\n",
      "2019-01-04  5.96  5.73  5.73   5.93  34666300.0       5.93\n",
      "2019-01-07  6.09  5.93  5.95   6.02  25502600.0       6.02\n",
      "2019-01-08  6.16  6.03  6.07   6.15  33497100.0       6.15\n",
      "2019-01-09  6.24  6.14  6.16   6.21  25471600.0       6.21\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from pandas  import Series, DataFrame\n",
    "\n",
    "import pandas_datareader as pdr\n",
    "import pandas_datareader.data as web\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# %matplotlib inline\n",
    "\n",
    "import datetime\n",
    "\n",
    "start = datetime.datetime(2017,1,1)\n",
    "end = datetime.date.today()\n",
    "# stock = web.DataReader(\"600519.SS\", \"yahoo\", start, end)\n",
    "stock = web.DataReader(\"NOK\", \"yahoo\", start, end)\n",
    "#print(stock)\n",
    "print(stock.head())\n",
    "print(stock.tail())\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###2. 打印"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-01-03', '2017-01-04', '2017-01-05', '2017-01-06',\n",
       "               '2017-01-09', '2017-01-10', '2017-01-11', '2017-01-12',\n",
       "               '2017-01-13', '2017-01-17',\n",
       "               ...\n",
       "               '2018-12-26', '2018-12-27', '2018-12-28', '2018-12-31',\n",
       "               '2019-01-02', '2019-01-03', '2019-01-04', '2019-01-07',\n",
       "               '2019-01-08', '2019-01-09'],\n",
       "              dtype='datetime64[ns]', name='Date', length=508, freq=None)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['High', 'Low', 'Open', 'Close', 'Volume', 'Adj Close'], dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3 打印DataFrame的数据新装"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(508, 6)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4 打印数据是否缺失"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 508 entries, 2017-01-03 to 2019-01-09\n",
      "Data columns (total 6 columns):\n",
      "High         508 non-null float64\n",
      "Low          508 non-null float64\n",
      "Open         508 non-null float64\n",
      "Close        508 non-null float64\n",
      "Volume       508 non-null float64\n",
      "Adj Close    508 non-null float64\n",
      "dtypes: float64(6)\n",
      "memory usage: 27.8 KB\n"
     ]
    }
   ],
   "source": [
    "stock.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5. 打印DataFrame的统计情况，最小，最大"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>508.000000</td>\n",
       "      <td>508.000000</td>\n",
       "      <td>508.000000</td>\n",
       "      <td>508.000000</td>\n",
       "      <td>5.080000e+02</td>\n",
       "      <td>508.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.658110</td>\n",
       "      <td>5.572480</td>\n",
       "      <td>5.616594</td>\n",
       "      <td>5.614882</td>\n",
       "      <td>1.499350e+07</td>\n",
       "      <td>5.432133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.514925</td>\n",
       "      <td>0.509549</td>\n",
       "      <td>0.512642</td>\n",
       "      <td>0.513376</td>\n",
       "      <td>8.776036e+06</td>\n",
       "      <td>0.530964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.560000</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>4.540000</td>\n",
       "      <td>4.520000</td>\n",
       "      <td>3.136300e+06</td>\n",
       "      <td>4.215283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.290000</td>\n",
       "      <td>5.230000</td>\n",
       "      <td>5.267500</td>\n",
       "      <td>5.267500</td>\n",
       "      <td>9.511275e+06</td>\n",
       "      <td>4.993991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.705000</td>\n",
       "      <td>5.595000</td>\n",
       "      <td>5.640000</td>\n",
       "      <td>5.650000</td>\n",
       "      <td>1.276195e+07</td>\n",
       "      <td>5.550756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.032500</td>\n",
       "      <td>5.960000</td>\n",
       "      <td>5.990000</td>\n",
       "      <td>6.002500</td>\n",
       "      <td>1.782922e+07</td>\n",
       "      <td>5.858861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>6.650000</td>\n",
       "      <td>6.530000</td>\n",
       "      <td>6.640000</td>\n",
       "      <td>6.550000</td>\n",
       "      <td>7.536440e+07</td>\n",
       "      <td>6.291072</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             High         Low        Open       Close        Volume  \\\n",
       "count  508.000000  508.000000  508.000000  508.000000  5.080000e+02   \n",
       "mean     5.658110    5.572480    5.616594    5.614882  1.499350e+07   \n",
       "std      0.514925    0.509549    0.512642    0.513376  8.776036e+06   \n",
       "min      4.560000    4.500000    4.540000    4.520000  3.136300e+06   \n",
       "25%      5.290000    5.230000    5.267500    5.267500  9.511275e+06   \n",
       "50%      5.705000    5.595000    5.640000    5.650000  1.276195e+07   \n",
       "75%      6.032500    5.960000    5.990000    6.002500  1.782922e+07   \n",
       "max      6.650000    6.530000    6.640000    6.550000  7.536440e+07   \n",
       "\n",
       "        Adj Close  \n",
       "count  508.000000  \n",
       "mean     5.432133  \n",
       "std      0.530964  \n",
       "min      4.215283  \n",
       "25%      4.993991  \n",
       "50%      5.550756  \n",
       "75%      5.858861  \n",
       "max      6.291072  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6. 增加涨跌幅度（当日Close - 上日Close）/上一日Close * 100%\n",
    "#### (1) 添加一列change,存储当日股票价格与前一日收盘价格相比的涨幅数值。 就是当日Close 价格和上一日Close的差值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Change</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-03</th>\n",
       "      <td>4.79</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.76</td>\n",
       "      <td>4.77</td>\n",
       "      <td>7883000.0</td>\n",
       "      <td>4.448430</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>4.85</td>\n",
       "      <td>4.79</td>\n",
       "      <td>4.80</td>\n",
       "      <td>4.84</td>\n",
       "      <td>10247100.0</td>\n",
       "      <td>4.513710</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>4.92</td>\n",
       "      <td>4.83</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.90</td>\n",
       "      <td>9878400.0</td>\n",
       "      <td>4.569665</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>4.99</td>\n",
       "      <td>4.90</td>\n",
       "      <td>4.93</td>\n",
       "      <td>4.92</td>\n",
       "      <td>18078800.0</td>\n",
       "      <td>4.588317</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>4.88</td>\n",
       "      <td>4.78</td>\n",
       "      <td>4.86</td>\n",
       "      <td>4.83</td>\n",
       "      <td>14554000.0</td>\n",
       "      <td>4.504384</td>\n",
       "      <td>-0.09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            High   Low  Open  Close      Volume  Adj Close  Change\n",
       "Date                                                              \n",
       "2017-01-03  4.79  4.75  4.76   4.77   7883000.0   4.448430     NaN\n",
       "2017-01-04  4.85  4.79  4.80   4.84  10247100.0   4.513710    0.07\n",
       "2017-01-05  4.92  4.83  4.85   4.90   9878400.0   4.569665    0.06\n",
       "2017-01-06  4.99  4.90  4.93   4.92  18078800.0   4.588317    0.02\n",
       "2017-01-09  4.88  4.78  4.86   4.83  14554000.0   4.504384   -0.09"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "change = stock.Close.diff()\n",
    "stock['Change'] = change\n",
    "stock.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (2) 对 缺失的数据去掉"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "change.fillna(change.mean(),inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Change</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-03</th>\n",
       "      <td>4.79</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.76</td>\n",
       "      <td>4.77</td>\n",
       "      <td>7883000.0</td>\n",
       "      <td>4.448430</td>\n",
       "      <td>0.00284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>4.85</td>\n",
       "      <td>4.79</td>\n",
       "      <td>4.80</td>\n",
       "      <td>4.84</td>\n",
       "      <td>10247100.0</td>\n",
       "      <td>4.513710</td>\n",
       "      <td>0.07000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>4.92</td>\n",
       "      <td>4.83</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.90</td>\n",
       "      <td>9878400.0</td>\n",
       "      <td>4.569665</td>\n",
       "      <td>0.06000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>4.99</td>\n",
       "      <td>4.90</td>\n",
       "      <td>4.93</td>\n",
       "      <td>4.92</td>\n",
       "      <td>18078800.0</td>\n",
       "      <td>4.588317</td>\n",
       "      <td>0.02000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>4.88</td>\n",
       "      <td>4.78</td>\n",
       "      <td>4.86</td>\n",
       "      <td>4.83</td>\n",
       "      <td>14554000.0</td>\n",
       "      <td>4.504384</td>\n",
       "      <td>-0.09000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            High   Low  Open  Close      Volume  Adj Close   Change\n",
       "Date                                                               \n",
       "2017-01-03  4.79  4.75  4.76   4.77   7883000.0   4.448430  0.00284\n",
       "2017-01-04  4.85  4.79  4.80   4.84  10247100.0   4.513710  0.07000\n",
       "2017-01-05  4.92  4.83  4.85   4.90   9878400.0   4.569665  0.06000\n",
       "2017-01-06  4.99  4.90  4.93   4.92  18078800.0   4.588317  0.02000\n",
       "2017-01-09  4.88  4.78  4.86   4.83  14554000.0   4.504384 -0.09000"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "change = stock.Close.diff()\n",
    "change.fillna(change.mean(),inplace=True)\n",
    "stock['Change'] = change\n",
    "stock.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### （3）计算涨跌幅度， pct_change() ： 第二项开始向前做减法，再除以第一项"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Change</th>\n",
       "      <th>pct_change</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-03</th>\n",
       "      <td>4.79</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.76</td>\n",
       "      <td>4.77</td>\n",
       "      <td>7883000.0</td>\n",
       "      <td>4.448430</td>\n",
       "      <td>0.00284</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>4.85</td>\n",
       "      <td>4.79</td>\n",
       "      <td>4.80</td>\n",
       "      <td>4.84</td>\n",
       "      <td>10247100.0</td>\n",
       "      <td>4.513710</td>\n",
       "      <td>0.07000</td>\n",
       "      <td>0.014675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>4.92</td>\n",
       "      <td>4.83</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.90</td>\n",
       "      <td>9878400.0</td>\n",
       "      <td>4.569665</td>\n",
       "      <td>0.06000</td>\n",
       "      <td>0.012397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>4.99</td>\n",
       "      <td>4.90</td>\n",
       "      <td>4.93</td>\n",
       "      <td>4.92</td>\n",
       "      <td>18078800.0</td>\n",
       "      <td>4.588317</td>\n",
       "      <td>0.02000</td>\n",
       "      <td>0.004082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>4.88</td>\n",
       "      <td>4.78</td>\n",
       "      <td>4.86</td>\n",
       "      <td>4.83</td>\n",
       "      <td>14554000.0</td>\n",
       "      <td>4.504384</td>\n",
       "      <td>-0.09000</td>\n",
       "      <td>-0.018293</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            High   Low  Open  Close      Volume  Adj Close   Change  \\\n",
       "Date                                                                  \n",
       "2017-01-03  4.79  4.75  4.76   4.77   7883000.0   4.448430  0.00284   \n",
       "2017-01-04  4.85  4.79  4.80   4.84  10247100.0   4.513710  0.07000   \n",
       "2017-01-05  4.92  4.83  4.85   4.90   9878400.0   4.569665  0.06000   \n",
       "2017-01-06  4.99  4.90  4.93   4.92  18078800.0   4.588317  0.02000   \n",
       "2017-01-09  4.88  4.78  4.86   4.83  14554000.0   4.504384 -0.09000   \n",
       "\n",
       "            pct_change  \n",
       "Date                    \n",
       "2017-01-03         NaN  \n",
       "2017-01-04    0.014675  \n",
       "2017-01-05    0.012397  \n",
       "2017-01-06    0.004082  \n",
       "2017-01-09   -0.018293  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock['pct_change'] = (stock['Change']/stock['Close'].shift(1))\n",
    "stock['pct_change'] = stock.Close.pct_change()\n",
    "stock.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
